The philosophical theory of scientific explanation proposed here involves a radically new treatment of causality that accords with the pervasively statistical character of contemporary science. Wesley C. Salmon describes three fundamental conceptions of scientific explanation--the epistemic, modal, and ontic. He argues that the prevailing view (a version of the epistemic conception) is untenable and that the modal conception is scientifically out-dated. Significantly revising aspects of his earlier work, he defends a causal/mechanical theory that is a version of the ontic conception. Professor Salmon's theory furnishes a robust argument for scientific realism akin to the argument that convinced twentieth-century physical scientists of the existence of atoms and molecules. To do justice to such notions as irreducibly statistical laws and statistical explanation, he offers a novel account of physical randomness. The transition from the "reviewed view" of scientific explanation (that explanations are arguments) to the causal/mechanical model requires fundamental rethinking of basic explanatory concepts.

Not all scientific explanations work by describing causal connections between events or the world's overall causal structure. In addition, mathematicians regard some proofs as explaining why the theorems being proved do in fact hold. This book proposes new philosophical accounts of many kinds of non-causal explanations in science and mathematics.

As Aristotle stated, scientific explanation is based on deductive argument--yet, Wesley C. Salmon points out, not all deductive arguments are qualified explanations. The validity of the explanation must itself be examined. Four Decades of Scientific Explanation provides a comprehensive account of the developments in scientific explanation that transpired in the last four decades of the twentieth century. It continues to stand as the most comprehensive treatment of the writings on the subject during these years. Building on the historic 1948 essay by Carl G. Hempel and Paul Oppenheim, "Studies in the Logic of Explanation,” which introduced the deductive-nomological (D-N) model on which most work on scientific explanation was based for the following four decades, Salmon goes beyond this model's inherent basis of describing empirical knowledge to tells us “not only what, but also why.” Salmon examines the predominant models in chronological order and describes their development, refinement, and criticism or rejection. Four Decades of Scientific Explanation underscores the need for a consensus of approach and ongoing evaluations of methodology in scientific explanation, with the goal of providing a better understanding of natural phenomena.

According to modern physics, many objectively improbable events actually occur, such as the spontaneous disintegration of radioactive atoms. Because of high levels of improbability, scientists are often at a loss to explain such phenomena. In this main essay of this book, Wesley Salmon offers a solution to scientific explanation based on the concept of statistical relevance (the S-R model). In this vein, the other two essays herein discuss "Statistical Relevance vs. Statistical Inference," and "Explanation and Information."

Scientific Explanation was first published in 1962. Minnesota Archive Editions uses digital technology to make long-unavailable books once again accessible, and are published unaltered from the original University of Minnesota Press editions. Is a new consensus emerging in the philosophy of science? The nine distinguished contributors to this volume apply that question to the realm of scientific explanation and, although their conclusions vary, they agree in one respect: there definitely was an old consensus. Co-editor Wesley Salmon's opening essay, "Four Decades of Scientific Explanation," grounds the entire discussion. His point of departure is the founding document of the old consensus: a 1948 paper by Carl G. Hempel and Paul Oppenheim, "Studies in the Logic of Explanation," that set forth, with remarkable clarity, a mode of argument that came to be known as the deductive-nomological model. This approach, holding that explanation dies not move beyond the sphere of empirical knowledge, remained dominant during the hegemony of logical empiricism from 1950 to 1975. Salmon traces in detail the rise and breakup of the old consensus, and examines the degree to which there is, if not a new consensus, at least a kind of reconciliation on this issue among contemporary philosophers of science and clear agreement that science can indeed tell us why. The other contributors, in the order of their presentations, are: Peter Railton, Matti Sintonen, Paul W. Humphreys, David Papineau, Nancy Cartwright, James Woodward, Merrilee H. Salmon, and Philip Kitcher.

A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.

This book explores the role of causal constraints in science, shifting our attention from causal relations between individual events--the focus of most philosophical treatments of causation—to a broad family of concepts and principles generating constraints on possible change. Yemima Ben-Menahem looks at determinism, locality, stability, symmetry principles, conservation laws, and the principle of least action—causal constraints that serve to distinguish events and processes that our best scientific theories mandate or allow from those they rule out. Ben-Menahem's approach reveals that causation is just as relevant to explaining why certain events fail to occur as it is to explaining events that do occur. She investigates the conceptual differences between, and interrelations of, members of the causal family, thereby clarifying problems at the heart of the philosophy of science. Ben-Menahem argues that the distinction between determinism and stability is pertinent to the philosophy of history and the foundations of statistical mechanics, and that the interplay of determinism and locality is crucial for understanding quantum mechanics. Providing historical perspective, she traces the causal constraints of contemporary science to traditional intuitions about causation, and demonstrates how the teleological appearance of some constraints is explained away in current scientific theories such as quantum mechanics. Causation in Science represents a bold challenge to both causal eliminativism and causal reductionism—the notions that causation has no place in science and that higher-level causal claims are reducible to the causal claims of fundamental physics.